安全可靠机器人运动规划的MPC框架

Moritz Eckhoff, R. J. Kirschner, Elena Kern, Saeed Abdolshah, S. Haddadin
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引用次数: 5

摘要

安全人机交互(HRI)策略,如完善的安全运动单元,为生物力学安全机器人运动提供了速度尺度。此外,可靠的HRI需要基于心理学的安全方法。这种方案可能是非常保守的,并且在机器人运动规划中,符合这种安全方法的机器人运动应该是时间有效的。在本研究中,我们通过模型预测控制机器人运动规划器提高了先前引入的基于心理的HRI安全方法的效率,该计划器同时调整笛卡尔路径和速度,以尽可能快地减少到目标姿势的距离。一个下属的实时运动发生器通过集成安全运动单元来保证人体的人身安全。通过两个实验验证了该运动规划器的有效性。在兼顾人的身心安全的前提下,通过路径和速度的同步调整,实现了高效的机器人运动。与直接路径速度缩放方法相比,我们的规划器使运动执行速度提高了28%。
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An MPC Framework For Planning Safe & Trustworthy Robot Motions
Strategies for safe human-robot interaction (HRI), such as the well-established Safe Motion Unit, provide a velocity scaling for biomechanically safe robot motion. In addition, psychologically-based safety approaches are required for trustworthy HRI. Such schemes can be very conservative and robot motion complying with such safety approaches should be time efficient within the robot motion planning. In this study, we improve the efficiency of a previously introduced approach for psychologically-based safety in HRI via a Model Predictive Control robot motion planner that simultaneously adjusts Cartesian path and speed to minimise the distance to the target pose as fast as possible. A subordinate real-time motion generator ensures human physical safety by integrating the Safe Motion Unit. Our motion planner is validated by two experiments. The simultaneous adjustment of path and velocity accomplishes highly time efficient robot motion, while considering the human physical and psychological safety. Compared to direct path velocity scaling approaches our planner enables 28 % faster motion execution.
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